The Support Vector Machine (SVM) model is the preferred classifier. It achieved the highest overall accuracy (0.993), the lowest error rate (0.007), and the highest agreement beyond chance as measured by Cohen’s kappa. Although logistic regression performed similarly, SVM provided slightly better classification performance. Naive Bayes showed lower accuracy and kappa values, making it less optimal for this dataset. Therefore, SVM is selected as the best-performing model.
